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Order parameter, free energy, and phase transitions

2009· book-chapter· en· W153238225 on OpenAlexaff
Rashmi C. Desai, Raymond Kapral

Bibliographic record

VenueCambridge University Press eBooks · 2009
Typebook-chapter
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhase diagramPhase (matter)ThermodynamicsMetastabilityBinary systemMaterials scienceBinodalBinary numberPhase transitionFerromagnetismChemical physicsHomogeneousCondensed matter physicsChemistryPhysicsMathematics

Abstract

fetched live from OpenAlex

The kinetics of first-order phase transitions involves the separation of an initially one-phase system into two coexisting phases. The formation and coarsening of domains of the coexisting phases as the system evolves are of central interest. The phase segregation process is usually studied by first preparing the system in a region of the phase diagram where the homogeneous state is stable. The system is then suddenly quenched into the two-phase region, and segregation into domains of the two stable phases takes place. Such phase segregation arises in a variety of physical contexts, including binary alloys and fluid mixtures, ferromagnetic systems, superfluids, polymer mixtures, and chemically reacting fluids. The temperature– composition (T, c) phase diagram for a binary mixture composed of constituents A and B is shown in Fig. 2.1. For low enough temperatures, in the region bounded by the coexistence curve the binary mixture will segregate into A-rich and B-rich phases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.198
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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